2018 Computation and Visualization Workshop

Summer Workshop for Science1 Faculty and Instructors

Working Schedule

A working schedule will be maintained here during the workshop. This will include links to presentations and resources from the workshop.

Feedback and Questions

We have created a Feedback and Questions google doc with questions (and answers) about the workshop.

Participants

We also have a Participants Info Doc where you can introduce yourself to the rest of the group.

What will we do?

The short answer is that we don’t know – at least not exactly. You will have ample opportunity to shape the workshop as we go along

  • by choosing which of parallel sessions you want to attend
  • by suggesting topics you would like to learn about
  • by selecting a project to work on

Some of the things on offer include

  • An introduction to the RStudio environment
  • A “Doing More with Less Cookbook” for R
  • Designing and creating sophisticated graphical data visualizations
  • Data wrangling: Manipulating data for graphics and insight
  • Preparing documents that include text, static and dynamic graphics, and analysis
  • Planning and developing of case studies (individually or in small groups)

In order to support project development, participants will learn specific skills as needed including topics such as:

  • Summarizing data with models
    • how to construct plausible models and fit them
    • displaying models on graphics
    • displaying inferential ideas on graphs
  • Basic data scraping skills (how to get data from web sites)
  • Connecting to and working with large databases in R
  • More advanced data cleaning skills
  • Additional programming skills
  • Resampling and bootstrap methods
  • Creating maps in R
  • etc, etc.

All aspects of the workshop will be “hands on.” The workshop leaders include several nationally recognized educators in data, graphics, and statistics. You provide the subject-matter expertise, we’ll help you exploit the power of modern compuation.

In your classes …

A major purpose of the second half of the workshop is to provide advice and help in setting up a data visualization/computing project for you to use in your own classes. The tools you will learn are powerful enough that you will be able to create a substantial project during the workshop, and will need just a few hours to tune it up when you get home.

New York City Weather

New York City Weather

A data graphic made with the powerful tools used in the CVC workshop: R, ggplot2 and dplyr.

CVC projects from Summer 2016 included

  • An analysis of Donald Trump’s tweets.
  • Streamlining the import of seismic waveform data into R and the combination of sound and spectral analysis to identify harmonic signals in seismic data.
  • US maps of service priorities (Medical, housing, advocacy, legal, etc.) after instances of intimate partner violence.
  • Large project in an upper-level Plant Physiology course/lab.
  • Analysis for a plant genomics research project.
  • Creating better graphs and tests for the data parts of a textbook using U.S. Census data.
  • RMarkdown code for class exercises in Into Biostats (based on examples from Analysis of Biological Data by Whitlock and Shluter).
  • College enrollment analysis
  • New R Programming Course Development
  • Plot from a data frame using Shiny and Plotly
  • Developing a microarray data wrangling workflow in R Markdown
  • Analysis of correlation between bird diving depth and surface temperature.
  • Residential Solar PV Deployment in Massachusetts.
  • Class materials for a new data visualization course.
  • Creating R package for the ISCAM materials.
  • Preparing R Markdown files for a Regression course.
  • Analysis of frog statistics as collected by FrogWatch for use in a first course in Environmental Science.
  • A Guide for Students to Make Plots in R Studio using ggplot2.
  • A Shiny app that asks the user to upload a file, select data columns and label column, and generate a 3d PCA plot accordingly.
  • Phylogenetics: retrieve sequence data from GenBank, generate tree, visualize tree.
  • Plot specimen localities (lat/long) and elevation using leaflet and ggmap.
  • Rmarkdown files for use in chemical analysis class to do some basic statistics, graphing, and linear regression.
  • Analysis of institutional data about student cohorts entering college between 2002-2013.
  • Displaying the latest reported Zika virus numbers on US Map

  1. We construe “science” broadly to include the natural and social sciences, as well as statistics, mathematics, and computer science. If you teach and want to integrate the use of data into your classes, this workshop is for you!↩